In order to search a desired piece of content out of a large number of pieces of content stored in a server, several methods have been introduced for presenting plural related keywords from a searching device. Here, each of the related keywords is a word (keyword) which is related to a word specified by a user (keyword). A degree of relevance among mutually related keywords is typically calculated based on the number of co-occurrence times among the keywords and appearance frequency thereof.
Such a searching device updates relevancy among the keywords for presenting a related keyword, upon updating data of a content database in which content is stored (See Patent Reference 1, for example). Thus, the searching device presents to the user a related keyword based on a current content stored in the content database.
However, the related keyword, recalled by a specific keyword by the user, is different from user to user. For example, a user who has watched only a currently broadcasted drama on which an “actor A” appears recalls an “actress B” who has appeared on the drama as a related keyword. Meanwhile, another user who watched only a drama broadcasted one year ago with the “actor A” appeared on recalls an “actress C” who appeared on the drama as a related keyword. In the case where each user has different knowledge, as described above, the related keyword by which each user recalls the “actor A” is possibly different. In other words, when the searching device presents only a related keyword generated based on a current content, some users may find an un-recallable related keyword. The resulting problem is that the user cannot select a keyword, and thus cannot narrow down content.
One of conventional methods for solving the problem is to classify all pieces of content, stored in the content database, according to time segments of fixed times. This allows the searching device using the method in Patent Reference 2 to establish relevancy among keywords for each time segment. As a result, the searching device can present to the user a related keyword generated based on relevancy of a different time segment for each of several time segments. As a keyword which relates to the “actor A”, for example, the searching device can simultaneously present to the user the “actress B” which has great relevance to a piece of content of this year and the “actress C” which has great relevance to another piece of content of the past year. As described above, the searching device presents the related keywords over several time segments, so that the user can select a related keyword to match with his or her knowledge. In other words, the user can efficiently narrow down pieces of content by repeating the selections of the related keyword.    Patent Reference 1: Japanese Unexamined Patent Application Publication No. 2007-188225    Patent Reference 2: Japanese Unexamined Patent Application Publication No. 2002-183175